Triple
T13349905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1947 Kenneth Arnold sighting |
E318042
|
entity |
| Predicate | hasMediaImpact |
P41061
|
FINISHED |
| Object | popularized the term "flying saucer" |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: popularized the term "flying saucer" | Statement: [1947 Kenneth Arnold sighting, hasMediaImpact, popularized the term "flying saucer"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaImpact Context triple: [1947 Kenneth Arnold sighting, hasMediaImpact, popularized the term "flying saucer"]
-
A.
mediaInfluence
chosen
Indicates that one entity affects, shapes, or alters another entity’s attitudes, behaviors, or perceptions through media content or channels.
-
B.
hasMediaCoverageLevel
Indicates the degree or extent to which something is covered or reported on by media outlets.
-
C.
hasStatusInMedia
Indicates that an entity is portrayed with a particular status or condition within a specific media work or context.
-
D.
hasRepresentationInMedia
Indicates that something is depicted, portrayed, or otherwise represented within a particular medium or media work.
-
E.
hasMediaCoverageSince
Indicates that an entity has had media coverage starting from a specified point in time and continuing from then onward.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.